In this episode of Inside Cancer Careers, we hear from Dr. Eytan Ruppin, Dr. Tiangen Chang, and Dr. Yingying Cao, computational scientists at NCI's Center for Cancer Research. They discuss their newly developed AI tool, LORIS, which can predict how a patient will respond to immunotherapy. LORIS analyzes six variables commonly measured in clinical settings to calculate a score indicating the patient's likelihood of response. They also share insights into the future of AI in cancer research and their career paths in science and offer advice to those interested in pursuing careers in biology, medicine, and computer science.

SHOW NOTES
Eytan Ruppin, M.D., Ph.D.
Tiangen Chang, Ph.D.
Yingying Cao, Ph.D.
Cancer Data Science Laboratory
NCI Center for Cancer Research (CCR)
Chang, TG., Cao, Y., Sfreddo, H.J. et al. LORIS robustly predicts patient outcomes with immune checkpoint blockade therapy using common clinical, pathologic and genomic features. Nat Cancer (2024)
LOgistic Regression-based Immunotherapy-response Score (LORIS)
Escher, Gödel, Bach: An Eternal Golden Braid by Douglas Hofstadter

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